Forensic PSHA: Benchmarking Canada’s Fifth Generation seismic hazard model using the OpenQuake‐engine
Bibliographic record
Abstract
This article explores the implementation of the Natural Resources Canada’s Fifth Generation national seismic hazard model as developed for the National Building Code of Canada (NBCC), within the OpenQuake‐engine. It also describes the reconciliation of the differences in hazard estimates relative to the published NBCC values, calculated using GSCFRISK. Source and ground‐motion input models developed for the GSCFRISK software were translated to the OpenQuake‐engine format for the hazard comparison. In order to successfully undertake this process, several adjustments to the OpenQuake code were needed to mimic the behavior of GSCFRISK. This required the development of new functions for earthquake‐rupture scaling and ground‐motion interpolation. Hazard values estimated using the OpenQuake‐engine are generally in good agreement with the 2015 NBCC national‐scale hazard values, with differences less than 2%–3% typically achieved. Where larger differences arise, they can be rationalized in terms of differences between the behaviors of the two software engines with respect to earthquake‐rupture length uncertainty and maximum ground‐motion integration distance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".